prepaw_bet2026

Pre-PAW

2026 WCPO Bigeye Assessment

Identify issues and priorities

Kyuhan Kim | SPC-OFP

13 November 2025

Why This Pre-PAW?

Context

SC19 Response (WCPFC 2023)
- 14 research recommendations
- Provide roadmap for 2026
2023 Status: Model instability remains
- Despite methodological improvements

Today’s Goals

1. Review 2023 Issues - What went well, what didn’t

2. Identify Priorities for 2026 - Must address vs nice-to-have

3. Key Decisions - Spatial: 6R vs 9R? - Tag mixing: 1Q/2Q/3Q? - Indonesia catch treatment

Part 1: 2023 Assessment Review

What We Learned

2023 Stock Status

Stock is Healthy

SB/SBF=0 = 0.35 (0.30-0.40)
- Above limit reference point
F/FMSY = 0.59 (0.46-0.74)
- Below target
Status: NOT overfished, NOT overfishing

But Model is Unstable

54-model grid shows:
- Wide uncertainty ranges
- Variable recruitment estimates
- Inconsistent biomass trends
SC19: “instability appears to remain”

2023 Catch Trends

WCPO BET Annual Catches (1952-2021)

Recent: ~140,000 mt/year (2010s-2021)
Peak: ~180,000 mt in early 2000s

By Gear Type:

Longline: 60-70% of total catch
- Dominant until late 1970s, then PS started increasing
Purse Seine: 20-30%
- Increased since early 1980s
Philippines/Indonesia Misc: 10-15%
- Handline, gillnet, other gears

Trend: Relatively stable since 2000

Annual catches by gear type (Day et al. 2023)

Catch by Region

Regional Distribution

Tropical regions dominate:

Regions 3, 4, 7, 8: 80-90% of total
- Equatorial zone (10°S - 10°N)
Region 7 (Indonesia/Philippines/Vietnam)
- Largest contributor
- 30-40% of WCPO catch
Temperate regions (1, 2, 5, 6)
- Seasonal fisheries
- Relatively stable over time

Key Concern

Region 7: Poor operational data
- Catches aggregated evenly across quarters/cells
- Major source of uncertainty

Annual catches by region (Day et al. 2023)

2023 Assessment: Model Improvements

Major Changes from 2020

Catch-conditioned model (Day et al. 2023): - Reduced from 11,421 to 3,067 parameters - More stable convergence

sdmTMB CPUE standardization (Teears et al. 2023): - Spatial-temporal modeling framework - Replaced VAST approach

Lorenzen natural mortality (Lorenzen 1996): - Size/age-dependent M scaling - More realistic mortality patterns

Internal growth estimation (Farley et al. 2020): - Von Bertalanffy parameters estimated - 1,004 otoliths incorporated

Independent Review Integration

Punt et al. (2023) (Punt, Maunder, and Ianelli 2023): - Reviewed 2020 YFT assessment - SC19 decision: Apply to BET where practical

Key recommendations implemented: - Revised tagger effects modeling (Peatman, Scutt Phillips, J., and Nicol 2023) - Tag mixing period as grid axis - Size composition reweighting methods - Growth-M correlation handling

Rigorous Convergence Process

Extensive jittering (Day et al. 2023): - Up to 60 runs per model to find global optimum - Diagnostic model achieved positive definite Hessian - 48 of 54 grid models converged

2023 Assessment: Results & Uncertainty

Stock Status (2021)

SB/SB_F=0 = 34% (Day et al. 2023): - Just below LRP (40%) - Median across 54-model grid

Fishing mortality above F_MSY: - Overfishing occurring - Primarily from purse seine associated sets

Recruitment stable since 1960: - ~120 million fish/year - No evidence of recruitment impairment

Data Inputs

Time series: 1952-2021 (70 years)

Size compositions: 41 fisheries

Tagging: ~67K BET (RTTP, PTTP, JPTP)

CPUE: Longline indices (9 regions)

Structural Uncertainty Grid

54 models exploring (Day et al. 2023): - Tag mixing: 1Q, 2Q, 3Q (most influential) - Steepness: 0.65, 0.80, 0.95 - Size comp weighting: 3 methods - Age data weighting: 6 levels

Remaining Challenges

High parameter uncertainty: - Correlations between M, growth, recruitment - Sensitivity to starting values

Key data limitations: 1. Limited age data (1,004 otoliths) 2. Spatial structure complexity (9 regions) 3. Size composition conflicts with tagging 4. Tag mixing period uncertain

SC19 Evaluation (WCPFC 2023):

“More rigorous… but model instability remains”

Result: 14 research recommendations

SC19’s 14 Research Recommendations

Data Collection & Quality

#1 Continue age & tagging data collection
#2 Develop additional CPUE index series
#3 Account for effort creep
#11 Review size composition representativeness
#12 Investigate weight vs tagging data inversion

Model Structure

#4 Simulation study: spatial structure (6-region)
#9 Identify correlated/sensitive parameters
#13 Reduce sensitivity to starting conditions

Biological Parameters

#5 Investigate unfished SSB increase (tropics)
#6 Yield-per-recruit analyses
#7 Evaluate growth/mortality variability
#10 Explore seasonal/regional growth

Diagnostics & Sensitivity

#8 Additional biological sensitivities
#14 Tag mixing diagnostics

Part 2: Critical Issues

7 Key Problems Identified

Issue #1: Age Data Quality

Problem

Only 1,004 otoliths aged — insufficient for internal growth estimation
High parameter uncertainty, affects biomass scaling
Limited spatial coverage

Impact

Cannot reliably estimate von Bertalanffy parameters
Growth-M correlation issues

SC19-#1, #7, #10

Continue age data collection; evaluate growth/mortality variability; explore regional traits

Sampling locations of fish aged (Day et al. 2023)

Issue #2: Spatial Structure

9-Region Problems

41 fisheries, 3,067 parameters, ~24-hour runtime
Persistent convergence issues (Hessian, correlations)
Model sensitivity to starting values (Parameter identifiability issues)

Evidence Supporting 6-Region

Biological data (Hamer et al. 2023): - Low tropical <-> temperate movement - High mixing within tropical/temperate zones - Size composition clustering supports simpler structure

Model performance: - 6-region used 2005-2011 successfully - Faster runtime, fewer parameters - Better convergence stability

SC19-#4

Simulation study: 6-region vs 9-region performance; “areas-as-fleets” approach

Issue #3: Indonesia Handline Data

Problem

2024 catch spike: Large increase in handline catch — major uncertainty in historical allocation

Data Quality

BET/YFT difficult to distinguish; no clear criteria
Port sampling only (<5%); no observers; no logbooks
Catches aggregated evenly across time/space

Impact

Major uncertainty in catch allocation
Large tropical biomass uncertainty
Size composition conflicts

SC19-#11

Comprehensive review of size composition representativeness and Region 7 fisheries

Issue #4: Tag Mixing Assumptions

Problem

Unknown mixing period (current: 2Q, more tests needed)
Varies by location, FAD vs free school, size, season

Impact

Most influential grid axis in 2023
Affects biomass scale, F-at-age patterns
Confounded with tag-reporting rates

Data: ~67K BET Tagged

RTTP (1989-92): 8.6K; PTTP (2006-20): 59K; JPTP (2000-20): added in 2020

SC19-#14

Develop diagnostics; test 1Q/2Q/3Q; quantify uncertainty (Peatman, Scutt Phillips, J., and Nicol 2023)

Issue #5: Size Composition Weighting

Problem

No iterative reweighting in 2023: - Fixed weights (no iterative weighting due to time constraints) - Data conflicts unresolved

Data Conflicts

Weight comp vs length/tagging pull opposite directions (Day et al. 2023)
“Inversion”: Weight -> higher biomass; length/tags -> lower biomass

Potential Causes

Unrepresentative sampling, coverage gaps
Selectivity/growth misspecification
Sampling observational errors or some conversion method issues

Impact

Biomass scale and reference point uncertainty

SC19-#11, #12

Review representativeness; investigate inversion

Issue #6: Unfished Biomass Trends

Problem

Tropical regions (3,4,7,8): unfished SSB increases over time — model artifact?

Potential Causes

Regional recruitment allocation patterns
Movement misspecification
Initial population distribution assumptions

Impact

Virgin biomass reference point uncertainty
Regional depletion estimates unreliable

SC19-#5

Investigate model specifications causing this trend

Fished vs Unfished SSB by region (Day et al. 2023)

Issue #7: Model Convergence

Problem & Results

Sensitivity to initial conditions — Models achieve suboptimal local minima

Diagnostic model: - Primary jittering (60x): Improvements of tens to hundreds of likelihood units - Stock status shifts: 5%+ in SB/SB_F=0

Grid models: - Before: 46/54 with PDH → After: 48/54 with PDH - Every model improved through jittering

SC19-#9, #13: Identify correlated/sensitive parameters; strategies to decrease starting value sensitivity

Key Findings (Day et al. 2023)

“Model convergence is a significant issue for these complex models… jittering is an important process to refine and improve the best solution.”

“Jittered solutions achieved improved objective function values and notable changes to derived management quantities. This was cause for considerable concern.”

“Every grid model improved through jittering — none was at a global minimum, even those 46 with positive definite Hessians.”

Part 3: Assessment Strategy

Proposed Approach

Foundation: 2023 Model

Retain Strong Elements

Model structure: - Catch-conditioned age-structured model - 9-region spatial framework - Quarterly time steps (1952-2021)

Key methodologies: - sdmTMB CPUE standardization - Lorenzen M-at-age scaling - Internally estimated von Bertalanffy growth - Extensive likelihood profiling

Independent Review

YFT review recommendations applied (Punt, Maunder, and Ianelli 2023): - Catch-conditioned framework - Internal growth estimation - Enhanced CPUE standardization - Improved convergence diagnostics

SC19 Evaluation

“The 2023 assessment applied a more rigorous approach to obtain a stable converged model than that applied in the 2020 assessment; however, model instability appears to remain.”

— SC19 Outcomes (WCPFC 2023)

Strengths recognized: - Comprehensive uncertainty grid - Extensive sensitivity testing - Improved convergence diagnostics

Remaining concerns: - Parameter convergence issues - Structural uncertainties

Path Forward

Address SC recommendations while: - Maintaining methodological strengths - Improving model stability - Expanding uncertainty characterization

Inputs Update (2022-2024)

Catch & Effort Data

Operational catches (2022-2024): - Longline fleets - Purse seine (associated/unassociated) - Domestic fisheries (Indonesia, Philippines, Vietnam)

Indonesia handline issue: - Large catch increase in 2024 - Gear allocation uncertainty (small -> large handline) - Historical series implications

CPUE indices (SC19-#2, #3) (WCPFC 2023): - sdmTMB standardization updated - Effort creep investigation - Additional index series tested

Size Composition Data

Reweighting methods (SC19-#11, #12) (WCPFC 2023; Punt, Maunder, and Ianelli 2023): - Francis method - Revisit Dirichlet-multinomial - Flag/fishery-specific weighting - Weight vs tag conflict investigation

Tagging Data

New tag returns (SC19-#1) (WCPFC 2023): - PTTP 2022-2024 recaptures - Tag-reporting rate updates (Peatman, Scutt Phillips, J., and Nicol 2023) - Mixing assumption refinement

Biological Data

Growth estimation (SC19-#7, #10) (WCPFC 2023): - Continue internal estimation - 1,004 otolith CAAL dataset - Regional/seasonal variation testing - Growth-mortality correlation

Additional Work

SC19-#5: Unfished SSB trend diagnostics

SC19-#6: Yield-per-recruit by fishery sector

Uncertainty Grid Design

2023 Grid Axes (54 models)

1. Steepness (Day et al. 2023): - 0.65 (pessimistic) - 0.80 (base) - 0.95 (optimistic)

2. Tag mixing (WCPFC 2023; Peatman, Scutt Phillips, J., and Nicol 2023): - 1 quarter - 2 quarters (base)

3. Size composition weighting (Peatman et al. 2023): - 10 (high weight) - 20 (base) - 40 (low weight)

4. Age composition weighting (Day et al. 2023): - 0.50 (low weight) - 0.75 (base) - 1.00 (high weight)

2026 Proposed Sensitivities

Spatial structure (SC19-#4) (WCPFC 2023; Hamer et al. 2023): - 6-region vs 9-region - Simulation study results (cross-fit tests: simulate from 9 -> fit 6, and vice versa)

Tag mixing period (SC19-#14): - 3 quarters (extended) - Piner plot validation

Structural: - Natural mortality scaling - Selectivity patterns

Data treatment: - Indonesia catch scenarios - CPUE effort creep - Size comp weighting schemes

Model Improvements

Convergence Strategy

SC19-#9 (WCPFC 2023): Identify problem parameters - Profile correlated parameters - Test parameter fixing options - Reduce dimensionality where possible

SC19-#13 (WCPFC 2023): Improve stability - Multiple starting values (jittering) (Day et al. 2023) - Phased parameter estimation - Hessian diagnostics at each step

Simplification Options

Consider reducing complexity (Punt, Maunder, and Ianelli 2023): - Spatial structure (6R vs 9R) (Hamer et al. 2023) - Fishery aggregations - Selectivity parameterization

Enhanced Diagnostics

Retrospective analysis (Punt, Maunder, and Ianelli 2023): - Peel test (5-10 years) - Mohns rho calculation - Pattern identification

Tag diagnostics (SC19-#14) (WCPFC 2023; Peatman, Scutt Phillips, J., and Nicol 2023): - Likelihood profile analysis - Tagger effects evaluation - Mixing period validation

Residual analysis (Day et al. 2023): - Size composition fits - CPUE index fits - Tag recovery patterns - Identify systematic patterns

Robustness Testing

Extensive testing (Day et al. 2023): - Self-consistency checks for a diagnostic model (possibly including a few key grid models depending on model run time) - Jittering to ensure global optimum

Discussion

What We Need to Decide

Key Questions

Decisions Needed

1. Spatial SC19-#4 - 9R vs 6R? - Both in grid?

2. Tag mixing SC19-#14 - Test 1Q, 2Q, 3Q? - All in grid or select one?

3. Growth SC19-#7 - Internal estimation? - Or external priors?

Guidance Needed

4. Indonesia catch - Accept 2024 spike? - Smooth transition? - Maintain historical?

5. Analysis priorities - CPUE effort creep? SC19-#3 - Yield-per-recruit? SC19-#6

Open Science & Reproducibility

Fully Open & Reproducible

All code and data publicly available:

Analysis code: github.com/PacificCommunity/ofp-sam-2026-BET
- MFCL model runs
- R/FLR4MFCL processing
- Diagnostic plots
Report compilation: github.com/PacificCommunity/ofp-sam-2026-BET-report
- Quarto source files
- This presentation
- Full documentation

Containerized Environment

Docker image for reproducibility:

Pre-built R environment with all dependencies
Ensures identical results across platforms
Available at: ghcr.io/pacificcommunity/bet-2026

Automated Workflows

GitHub Actions for quality control and continuous integration:

Automatic report compilation
- Every update on writing triggers rebuild, including figures
- Ensures report stays synchronized with analysis
Code testing
- Diagnostic model (with a single iteration in MFCL) runs on each commit
- Plot generation tested
- Reproducibility verified

Transparent Process

Benefits: - Community can review methods - Results fully reproducible - Facilitates review and collaboration - Supports future assessments

References

Day, J., A. Magnusson, T. Teears, J. Hampton, N. Davies, C. Castillo Jordán, T. Peatman, et al. 2023. “Stock Assessment of Bigeye Tuna in the Western and Central Pacific Ocean: 2023.” Working Paper SC19-SA-WP-05 (Rev. 2). Koror, Palau: Western; Central Pacific Fisheries Commission.

Farley, J., K. Krusic-Golub, P. Eveson, N. Clear, F. Roupsard, C. Sanchez, S. Nicol, and J. Hampton. 2020. “Age and Growth of Yellowfin and Bigeye Tuna in the Western and Central Pacific Ocean from Otoliths.” Working Paper SC16-SA-WP-02. Online: Western; Central Pacific Fisheries Commission.

Hamer, P., J. Macdonald, J. Potts, T. Vidal, T. Teears, and I. Senina. 2023. “Review and Analyses to Inform Conceptual Models of Population Structure and Spatial Stratification of Bigeye and Yellowfin Tuna Assessments in the Western and Central Pacific Ocean.” Working Paper SC19-SA-WP-02. Koror, Palau: Western; Central Pacific Fisheries Commission.

Lorenzen, K. 1996. “The Relationship Between Body Weight and Natural Mortality in Juvenile and Adult Fish: A Comparison of Natural Ecosystems and Aquaculture.” Journal of Fish Biology 49 (4): 627–42. https://doi.org/10.1111/j.1095-8649.1996.tb00060.x.

Peatman, T., J. Day, A. Magnusson, T. Teears, P. Williams, J. Hampton, and P. Hamer. 2023. “Analysis of Purse-Seine and Longline Size Frequency Data for the 2023 Bigeye and Yellowfin Assessments.” Information Paper SC19-SA-IP-03. Koror, Palau: Western; Central Pacific Fisheries Commission.

Peatman, T., Scutt Phillips, J., and S. Nicol. 2023. “Analysis of Tagging Data for the 2023 Bigeye and Yellowfin Tuna Assessments: Corrections to Tag Releases for Tagging Conditions.” Information Paper SC19-SA-IP-08. Koror, Palau: Western; Central Pacific Fisheries Commission.

Punt, André E., Mark N. Maunder, and James N. Ianelli. 2023. “Independent Review of Recent WCPO Yellowfin Tuna Assessment.” Working Paper SC19-SA-WP-01. Koror, Palau: Western; Central Pacific Fisheries Commission.

Teears, T., J. Day, J. Hampton, A. Magnusson, S. McKechnie, T. Peatman, Scutt-Phillips, J., P. Williams, and P. Hamer. 2023. “CPUE Analysis and Data Inputs for the 2023 Bigeye and Yellowfin Tuna Assessments in the WCPO.” Working Paper SC19-SA-WP-03 (Rev. 1). Koror, Palau: Western; Central Pacific Fisheries Commission.

WCPFC. 2023. “Summary Report of the Nineteenth Regular Session of the Scientific Committee.” Summary Report SC19. Koror, Palau: Western; Central Pacific Fisheries Commission.

Thank You

Questions & Discussion

All materials publicly available

Analysis: github.com/PacificCommunity/ofp-sam-2026-BET

Report: github.com/PacificCommunity/ofp-sam-2026-BET-report

Pacific Community (SPC)
Oceanic Fisheries Programme

Contact: kyuhank@spc.int